Fusion techniques for reliable information: A survey

International Journal of Digital Content Technology and its Applications

Volumn 4, Issue 2, 2010, Pages 74-88

  Lee, Hyun ^a   Lee, Byoungyong ^b   Park, Kyungseo ^a   Elmasri, Ramez ^a  

^a UNIVERSITY OF TEXAS AT ARLINGTON   (United States)

^b Korea Land and Housing Corporation   (South Korea)

Author keywords

Data; Fusion; Information; Multisensor; Pervasive and ubiquitous computing; Reliability; Survey; System performance

Indexed keywords

FUSION; INFORMATION; MULTI SENSOR; PERVASIVE AND UBIQUITOUS COMPUTING; SURVEY SYSTEMS;

DECISION MAKING; SURVEYS;

UBIQUITOUS COMPUTING;

EID: 77956961258     PISSN: 19759339     EISSN: None     Source Type: Journal    
DOI: 10.4156/jdcta.vol4.issue2.9     Document Type: Article

References (115)

1. R. A. Campbell and R. H. Campbell, "An infrastructure for context awareness based on first order logic," Personal and Ubiquitous Computing, Vol. 7, No. 6, 2003, pp. 353-364
2. S. Agarwal, A. Joshi, T. Finin, Y. Yesha and T. Ganous, "A pervasive computing system for the operating room of the future," Mobile Networks and Applications, Vol. 12, No. 2, 2007, pp. 215-228
3. K. Baclawski, M. Kokar, C. J. Matheus, J. Letkowski and M. Malczewski, "Formalization of situation awareness," the 11th OOPSLA workshop on Behaviors Semantics, 2002, pp. 1-15
4. C. A. Barlow, L. D. Stone, and M. V. Finn, "Unified data fusion," Proc. of the 9th National Symposium on Sensor Fusion, Vol. 1, 1996, pp. 321-330
5. O. Basir and X. Yuan, "Engine fault diagnosis based on multi-sensor information fusion using Dempster-Shafer evidence theory," Information Fusion, Vol. 8, No. 4, 2007, pp. 379-386
6. L. R. Beach, "Image theory: Decision Making in Personal & Organization Contexts," John Wiley & Sons Inc., 1990
7. M. Beiql, M. Beuster, D. Rohr, T. Riedel, C. Decker and A. Krohn, "S2b2: Blackboard for transparent data and control access in heterogeneous sensing systems," the 4th Intl. Conf. on Networked Sensing Systems (INSS), 2007, pp. 126-129
8. S. Benferhat, D. Dubois, S. Kaci, and H. Prade, "Bipolar possibility theory in preference modeling: representation, fusion and optimal solutions," Information Fusion, Vol. 7, No. 1, 2006, pp. 135-150
9. M. Beynon, B. Curry, and P. Morgan, "The Dempster-Shafer theory of evidence: an alternative approach to multicriteria decision modeling," Omega, Vol. 28, No. 1, 2000, pp. 37-50
10. E. Biglieri and M. Lops, "Multiuser detection using random-set theory," EUSIPCO 2006 Special Session on 'Multi-user MIMO Communications, 2006
11. P. K. Biswas, H. Qi, and Y. Xu, "Mobile-agent based collaborative sensor fusion," Information Fusion, Vol. 9, No. 3, 2008, pp. 399-411
12. S. Blackman and R. Popoli," Design and Analysis of Modern Tracking Systems," Artech House, 1999
13. E. Blasch, "Assembling information fused human computer cognitive decision making tool," IEEE Aerospace and Electronic Systems Magazine, 2000, pp. 11-17
14. E. Blasch, "Ontological issues in higher level of information fusion: User refinement of the fusion," the 6th Intl. Conf. on Information Fusion, 2003, pp. 634-641
15. N. A. Bomberger, A. M. Waxman, B. J. Rhodes, and N. A. Sheldon, "A new approach to higher-level information fusion using associative learning in semantic network of spiking neurons," Information Fusion, Vol. 8, No. 3, 2007, pp. 227-251
16. E. Bosse, J. Roy, and S. Paradis, "Modeling and simulation in support of design of a data fusion system," Information Fusion, Vol. 1, No. 2, 2000, pp. 77-87
17. E. Bosse, P. Valin, A. Boury-brisset, and D. Grenier, "Exploitation a priori knowledge for information fusion," Information Fusion, Vol. 7, No. 2, 2006, pp. 161-175
18. G. Brown, J. Wyatt, R. Harris, and X. Yao, "Diversity creation methods: a survey and categorization," Information Fusion, Vol. 6, No. 1, 2005, pp. 5-20
19. A. Bundy, "Incidence calculus: A mechanism for probabilistic reasoning," Journal of automated reasoning, Vol. 1, No. 3, 1985, pp. 263-283
20. D. A. Bushey and M. J. Forsyth, "The recognition-primed decision model: An alternative to the MDMP for GWOT," FA Journal, 2006
21. F. Campos and S. Calvalcante, "An extended approach for Dempster-Shafer theory," IEEE Intl. Conf. on Information Reuse and Integration, 2003, pp. 338-344
22. G. A. Carpenter, S. Martens, and O. J. Ogas, "Self-organizing hierarchical knowledge discovery: a new framework using ARTMAP neural networks," Neural Networks, Vol. 18, No. 3, 2005, pp. 287-295
23. C. Cayrol, V. Royer, and C. Saurel, "Management of preferences in assumption-based reasoning," Advanced Methods in AI (LNCS), Vol. 682, 1993, pp. 13-22
24. S. Chen and Y. W. Jen, "Data fusion neural network for tool condition monitoring in CNC milling machining," Intl. Journal of Machine Tools and Manufacture, Vol. 40, No. 3, 2000, pp. 381-400
25. L. Cholvy and A. Hunter, "Information fusion in logic: A brief overview," Qualitative and Quantitative Practical Reasoning (LNCS), Vol. 1244, 1997, pp. 86-95
26. J. Clark and A. Yullie, "Data fusion for sensory information processing system," Kluwer Academic Publication, 1990
27. B. Dasarathy, "Information fusion benefits delineation under off-nominal scenarios. Proc. of the SPIE, Vol. 3719, No. 2, 1999, pp. 2-13
28. B. Dasarathy, "Information fusion - what, where, why, when and how," Information Fusion, Vol. 2, No. 2, 2001, pp. 75-76
29. B. Dasarathy, "Fusion system: How good is it," Information Fusion, Vol. 2, No. 3, 2001, pp. 161-162
30. D. De-Brucg, O. Colot, and A. Sombo, "Identical foundation of probability theory and fuzzy set theory," the 5th Intl. Conf. on Information Fusion, Vol. 2, 2002, pp. 1442-1449
31. D. Desovski, Y. Liu, and B. Cukic, "Linear randomized voting algorithm for fault tolerant sensor fusion and the corresponding reliability model," IEEE Intl. symposium on High-Assurance Systems Engineering, 2005, pp. 153-162
32. J. Dezert and F. Smarandache, "An introduction to the DSm theory for the combination of paradoxical, uncertain and imprecise sources of information," Octagon Mathematical Magazine, Vol. 15, No. 2, 2005, pp. 681-722
33. D. Dubois and H. Prade, "Possibility theory, probability theory and multiple-valued logics: Clarification," Annals of Mathematics and AI, Vol. 32, No. 1-4, 2001, pp. 35-66
34. D. Dubois, H. Prade, and R. Sabbadin, "Decision-theoretic foundation of qualitative possibility theory," European Journal of Operational Research, Vol. 128, No. 3, 2001, pp. 459-478
35. M. R. Endsley, "Toward a theory of situation awareness in dynamic systems," Human Factors, Vol. 37, No. 1, 1995, pp. 32-64
36. J. Esteban, A. Starr, R. Willetts, P. Hannah, and P. Bryanston-Cross, "A review of data fusion models and architectures: Towards engineering guidelines," Neural Computing and Applications, Vol. 14, No. 4, 2005, pp. 273-281
37. V. K. Garg and V. Ogale, "Fusible data structures for fault tolerance," Proc. of 27th Intl. Conf. on Distributed Computing Systems, 2007, pp. 20-44
38. I. Goll and A. Rasheed, "Rational decision making & firm performance: the moderating role of environment," Strategic Management Journal, Vol. 18, No. 7, 1997, pp. 583-591
39. J. Gomes and H. Choi, "Adaptive optimization of join threes for multi-join queries over sensor streams," Information Fusion, Vol. 9, No. 3, 2008, pp. 412-424
40. I. Goodman, R. Mahler, and H. Nguyen, "Mathematics of data fusion," Kluwer Academic Publisher, 1997.
41. A. A. Goshtashby, "Image fusion: Advances in the state of the art," Information Fusion, Vol. 8, No. 2, 2007, pp. 114-118
42. D. L. Hall and J. Llinas, "An introduction to multisensor data fusion," the IEEE, Vol. 85, No. 1, 1997, pp. 6-23
43. D. L. Hall and S. McMullen, "Mathematical techniques in multisensor data fusion," Artech House, 2004
44. G. Hang and Y. Min, "Data fusion in distributed multi-sensor system," Geo-Spatial Information Science, Vol. 7, No. 3, 2004, pp. 214-217
45. X. Hong, "Valuation-based systems for decision analysis using belief functions," Decision Support Systems, Vol. 20, No. 2, 1997, pp. 165-184
46. H. Hu, S. Qian, J. Wang, and Z. Shi, "Application of information fusion technology in the remote state online monitoring and fault diagnosing system for power transformer," 8th Intl. Conf. on Electronic Measurement and Instruments, 2007, pp. 550-555
47. A. Hunter and W. Liu, "Fusion rules for merging uncertain information," Information Fusion, Vol. 7, No. 1, 2006, pp. 97-134
48. C. Kahraman, G. Buyukozkan, and N. Y. Ates, "A two phase multi-attribute decision making approach for new product introduction," Information Science: International Journal, Vol. 177, No. 7, 2007, pp. 1567-1582
49. A. Klausner, B. Rinner, and A. Teng, "I-sense: Intelligent embedded multi-sensor fusion," Proc. of Intl. workshop on intelligent solutions in embedded systems, 2006, pp. 1-12
50. J. Korbicz and M. Kowal, "Neuro-fuzzy networks and their application to fault detection of dynamical systems," Engineering Applications of AI journal, Vol. 20, No. 5, 2007, pp. 607-617
51. H. Lee, J. Choi, and R. Elmasri, "A classification and modeling of the quality of contextual information in smart spaces," 7th IEEE Intl. Conf. on Per Com Workshop on Context Modeling and Reasoning (CoMoRea), 2009.
52. H. Lee, J. Choi, and R. Elmasri, "A dynamic evidential network for multisensor context reasoning in home-based care," the IEEE 8th Intl. Conf. on Systems, Man, and Cybernetics (SMC 2009), 2009
53. H. Lee, J. Choi, and R. Elmasri, "Sensor data fusion using DSmT for activity recognition under uncertainty in home-based care," the IEEE 23rd Intl. Conf. on Advanced Information Networking and Applications, 2009
54. A. Lemmi and G. Betti, "Capability approach and fuzzy set theory: description, aggregation and inference issues," Fuzzy Set Approach to Multidimensional Poverty Measurement, 2006, pp. 93-113
55. D. Lewis, "Probabilities of conditionals and conditional probabilities," the Philosophical Review, Vol. 85, No. 3, 1976, pp. 297-315
56. J. Lindner, R. Murphy, and E. Nitz, "Learning the expected utility of sensor and algorithms," the IEEE Intl. Conf. on multisensor fusion and integration for intelligent systems, 1004, pp. 583-590
57. J. Llinas, C. Bowman, G. Rogova, A. Steinberg, and F. White, "Revisiting the JDL data fusion model II," the 7th Intl. Conf. on Information Fusion, 2004, pp. 1218-1230
58. C. Lu, Y. Ho, and L. Fu," Creating robust activity maps using wireless sensor network in a smart home," IEEE Intl. Conf. on Automation Science and Engineering, 2007, pp. 741-746
59. R. Luo, C. Yih, and K. Su, "Multisensor fusion and integration: approaches, applications, and future research directions," IEEE Sensors Journal, Vol. 2, No. 2, 2002, pp. 107-119
60. D. Macii, A. Boni, M. D. Cecco, and D. Petri, "Tutorial 14: Multisensor data fusion," IEEE Instrumentation and Measurement Magazine, Vol. 11, No. 3, 2008, pp. 24-33
61. D. Mandic, D. Obradovic, A. Kuh, T. Adali, U. Trutschel, M. Golz, P. Wilde, J. Barria, A. Constantinides, and J. Chambers, "Data fusion for modern engineering applications: An overview," Intl. Conf. on Artificial Neural Networks (LNCS), Vol. 3697, 2005, pp. 715-721
62. A. Martin and C. Osswald, "Toward a combination rule to deal with partial conflict and specificity in belief functions theory." 10th Intl. Conf. on Information Fusion, 2007, pp. 1-8
63. J. P. Matsuura and T. Yoneyama, "Learning Bayesian networks for fault detection," Proc. of 14th IEEE Signal Processing Workshop, 2004, pp. 133-142
64. C. McCullough, B. Dasarathy, and P. Lindberg, "Multilevel sensor fusion for improved target discrimination," Proc. of the 35th IEEE Decision and Control, Vol. 4, 1996, pp. 3674-3675
65. S. Mohammed and E. Ringseis, "Cognitive diversity and consensus in group decision making: The role of inputs, processes, and outcomes," Organizational Behavior and Human Decision Processes, Vol. 85, No. 2, 2001, pp. 310-335
66. A. Motro and P. Anokhin, "Fusionplex: Resolution of data inconsistencies in the integration of heterogeneous information sources," Information Fusion, Vol. 7, No. 2, 2006, pp. 176-196
67. Z. P. Mourelatos and J. Zhou, "Reliability estimation and design with insufficient data based on possibility theory," AIAA Journal, Vol. 43, No. 8, 2005, pp. 1696-1705
68. S. Mulgund, G. Rinkus, C. Illgen, and J. Friskie, "OLIPSA: On-line intelligent processor for situation assessment," the 2nd Annual Symposium and Exhibition on situational awareness in the tactical air environment, 1997.
69. K. Murphy, "Dynamic Bayesian network: representation, inference and learning," Ph. D. Dissertation, Univ. of California, Berkeley, 2002
70. E. F. Nakamura and A. Loureiro, "Information fusion in wireless sensor networks," Intl. Conf. on Management of data (ACM SIGMOD), 2008, pp. 1365-1372
71. G. W. Ng and K. H. Ng, "Sensor management - what, why and how," Information Fusion, Vol. 1, No. 2, 2000, pp. 67-75
72. N. C. Oza and K. Tumer, "Classifier ensembles: Select real-world applications," Information Fusion, Vol. 9, No. 1, 2008, pp. 4-20
73. G. Pallapa, N. Roy, and S. Das, "Precision: privacy enhanced context-aware information fusion in ubiquitous healthcare," 1st Intl. Workshop on Software Engineering for Pervasive Computing Applications, Systems, and Environments, 2007, pp. 1-10
74. J. Pansiot, D. Stoyanov, D. McIlwraith, B. Lo, and G. Z. Yang, "Ambient and wearable sensor fusion for activity recognition in healthcare monitoring systems," 4th Intl. Workshop on Wearable and Implantable Body sensor network, 2007, pp. 208-212
75. L. Paradis and Q. Han, "A survey of fault management in wireless sensor networks," Journal of Network and Systems Management, Vol. 15, No. 2, 2007, pp. 171-190
76. Y. Peng, C. Lin, and M. Sun, "A distributed multi-modality sensor system for home-used sleep condition inference and monitoring," 1st Trans-Disciplinary Conf. on Distributed Diagnosis and Home Healthcare, 2006, pp. 20-23
77. P. Perez, J. Vermaak, and A. Blake, "Data fusion for visual tracking with particles," the IEEE, Vol. 92, No. 3, 2004, pp. 495-513
78. L. Perlvsky, "Concurrent learning and fusion," Information Fusion, Vol. 8, No. 3, 2007, pp. 224-226
79. R. W. Pew and A. S. Mavor, "Modeling human and organizational behavior: application to military simulations," the National Academy Press, 1998
80. G. Phillips-Wren, N. Lchalkaranje, and L. Jain, "Intelligent decision making: An AI-based approach," Springer, 2008
81. R. Polikar, D. Parikh, and S. Mandayam, "Multiple classifier systems for multisensor data fusion," the IEEE Sensors Applications Symposium, 2006, pp. 180-184
82. R. Polikar, A. Topalis, D. Parikh, D. Green, J. Frymiare, J. Kounios, and C. Clark, "an ensemble based data fusion approach for early diagnosis of Alzheimer's disease," Information Fusion, Vol. 9, No. 1, 2008, pp. 83-95
83. S. Pop, O. Lavialle, R. Terebes, and M. Borda, "Low-level fusion: a PDE-based approach," 10th Intl. Conf. on Information Fusion, 2007, pp. 1-8
84. H. Z. Qiu, H. Y. Zhang, and H. Jin, "Fusion algorithm of correlated local estimates," Aerospace Science and Technology, Vol. 8, No. 7, 2004, pp. 619-626
85. J. Quiggin, "Regret theory with general choice sets," Journal of Risk and Uncertainty, Vol. 8, No. 2, 1994, pp. 153-165
86. R. Rajagopal, X. Nguyen, S. C. Ergen, and P. Varaiya, "Distributed online simultaneous fault detection for multiple sensors," Intl. Conf. on Information processing in sensor networks, 2008, pp. 133-144
87. G. L. Rogova and V. Nimier, "Reliability in information fusion: Literature survey," 7th Intl. Conf. on Information Fusion, 2004, pp. 1158-1165
88. E. Shahbazian, G. Rogova, and P. Valin, "Data fusion for situation monitoring, incident detection, alert and response management," NATO Science Series, 2005
89. L. Shoemaker, R. Banfield, L. Hall, K. Bowyer, and W. Kegelmeyer, "using classifier ensembles to label spatially disjoint data," Information Fusion, Vol. 9, No. 1, 2008, pp. 120-133
90. A. Shuster, "Intelligent computing everywhere," Springer, 2007
91. F. Smarandache and J. Dezert, "Qualitative belief conditioning rules," the 10th Intl. Conf. on Information Fusion, 2007, pp. 1-8
92. P. R. Smart, N. R. Shadbolt, L. Carr, and M. Schraefel, "Knowledge-based information fusion for improved situational awareness," the 8th Intl. Conf. on Information Fusion, Vol. 2, 2005, pp. 1-8
93. P. Smets, "Data fusion in the transferable belief model," the 3rd Intl. Conf. on Information Fusion, 2000, pp. 21-23
94. L. D. Stone, C. A. Barlow, and T. L. Corwin, "Bayesian multiple target tracking," Artech House, 1999
95. Y. Sun and L. Bentabet, "A sequential Monte-Carlo and DSmT based approach for conflict handling in case of multiple targets tracking," Image Analysis and Recognition (LNCS), Vol. 4633, 2007, pp. 526-537
96. R. J. Tait, A. Hopgood, and G. Sheaefer, "Registration and fusion of multi-sensor data using multiple agents," Proc. of SPIE, the Intl. Society for Optical Engineering, Vol. 5823, 2005, pp. 104-112
97. S. Thiriot and J. Kant, "Modeling one human decision maker with a multi-agent system: the CODAGE approach. Intl. Conf. on Autonomous Agents, 2006, pp. 50-57
98. J. Thomas, W. Center and Y. Height, "Visual data fusion for applications of high-resolution numerical weather prediction," the IEEE Visualization Conference, 2000, pp. 477-480
99. P. Todd and G. Gigerenzer, "Putting naturalistic decision making into the adaptive toolbox," Journal of Behavioral Decision Making, Vol. 14, No. 5, 2001, pp. 353-384
100. V. Torra and Y. Narukawa, "Modeling decisions," Springer, 2007
101. P. Varshney, "Multi-sensor data fusion," Electronics and Communication Engineering Journal, Vol. 9, No. 6, 1997, pp. 245-253
102. M. Vatas, R. Singh, A. Noore, and M. Houch, "Quality-augmented fusion of level-2 and level-3 fingerprint information using DSmT," the Intl. Journal of Approximate Reasoning, Vol. 50, No. 1, 2007, pp. 51-61
103. T. Vercauteren, D. Guo, and X. Wang, "Joint multiple target tracking and classification in collaborative sensor networks," the IEEE journal on Selected Areas in Communications, Vol. 23, No. 4, 2005, pp. 714-723
104. F. E. White, "A model for data fusion," the 1st National Symposium on Sensor Fusion, Vol. 2, 1988, pp. 149-158
105. H. Wu, M. Siegel, R. Stiefelhagen, and J. Yang, "Sensor fusion using Dempster-Shafer theory," 19th IEEE Conf. on Instrumentation and Measurement Technology, Vol. 1, 2002, pp. 7-12
106. J. K. Wu and Y. F. Wong, "Bayesian approach for data fusion in sensor networks," 9th Intl. Conf. on Information Fusion, 2006, pp. 1-5
107. N. Xiong and P. Svensson, "Multi-sensor management for information fusion: issues and approaches," Information Fusion, Vol. 3, No. 2, 2002, pp. 163-186
108. X. Xu, G. Ge, and C. Wen, "A fusion algorithm of multisensor system based on sequential filtering in distributed network," the IEEE Intl. Conf. on Automation and Logistics, 2007, pp. 2325-2328
109. Y. Xu, L. Wang, and Y. Sheng, "Rough set theory-based multi-class decision attribute reduction algorithm and its application," 5th IEEE Intl. Conf. on Cognitive Informatics, Vol. 2, 2006, pp. 722-725
110. Z. Yunmin and L. X. Rong, "Extended Dempster-Shafer combination rules based on random set theory," Proc. of SPIE, Multisensor and Multisource Information Fusion: Architectures, Algorithms, and Applications, Vol. 5434, 2004, pp. 112-120
111. L. A. Zadeh, "Toward a unified theory of uncertainty," IPMU conference, 2004
112. Y. Zhang and Q. Ji, "Active and dynamic information fusion for multi-sensor systems with dynamic Bayesian networks," IEEE Transaction on Systems, Mans, and Cybernetics, Vol. 36, No. 2, 2006, pp. 467-472
113. X. Zhao, S. Yuan, Z. Yu, W. Ye, and J. Cao, "Designing strategy for multi-agent system based large structural health monitoring," Expert Systems with Applications: An Intl. Journal, Vol. 34, No. 2, 2008, pp. 1154-1168
114. J. Zhou, Y. Zhu, Z. You, and E. Song, "An efficient algorithm for optimal linear estimation fusion in distributed multisensor systems," IEEE Transaction on Systems, and Man and Cybernetics, Vol. 36, No. 2, 2006, pp. 1000-1009
115. X. Zhou, D. Comaniciu, and A. Gupta, "An information fusion framework for robust shape tracking," IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. 27, No. 1, 2005, pp. 115-129